Computational Intelligence - IT8601

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Computational Intelligence

Computational Intelligence



UNIT I : INTRODUCTION

UNIT II : KNOWLEDGE REPRESENTATION AND REASONING

UNIT III : UNCERTAINTY

UNIT IV : LEARNING

UNIT V : INTELLIGENCE AND APPLICATIONS

For Extra Reference Notes 1


What is Artificial Intelligence?
History of Artificial Intelligence(AI)
Components of Artificial Intelligence(AI)
Definition of Artificial intelligence
Weak And Strong Artificial Intelligence(AI)
Areas and Task Domain of Artificial Intelligence(AI)
Artificial Intelligence(AI) Technique
7- Problem Characteristics
Production System: Characteristics, Features , Disadvantages
Algorithm of Problem Solving
Various Types of Artificial Intelligence Problems and their Solutions
Searching Algorithms - Artificial Intelligence(AI)
Uninformed Search
Breadth First Search (BFS): Concept, Implementation, Advantages, Disadvantages
Depth First Search (DFS): Concept, Implementation, Advantages, Disadvantages
Brute Force or Blind Search(BFS)
Greedy Search
Informed Search (Heuristic Search)
Best First Search: Concept, Algorithm, Implementation, Advantages, Disadvantages
Branch and Bound Search: Concept, Algorithm, Implementation, Advantages, Disadvantages
A* Search: Concept, Algorithm, Implementation, Advantages, Disadvantages
AO* Search(Graph): Concept, Algorithm, Implementation, Advantages, Disadvantages
Hill Climbing Search Algorithm: Concept, Algorithm, Advantages, Disadvantages
Knowledge Based Systems
Type of Knowledge
Knowledge Acquisition Techniques
Knowledge representation
Properties for knowledge Representation
Syntax and semantics for Knowledge Representation
Types of Knowledge Representation
Human Associative Memory (HAM)
MIN-MAX Search Algorithm
Constraint Satisfaction Search Algorithm
Planning
Basic Components of a Planning System
Planning in State Space Search
Various Planning Techniques
Understanding in Artificial Intelligence
Natural Language Processing
Goals, Applications and Examples of Natural Language Processing(NLP)
ELIZA, HAL, LUNAR, SHRDLU System
The Chomsky Hierarchy of Grammars
Transformational Grammar
Case Grammars (FILLMORE’s Grammar)
Semantic Grammars
Context Free Grammar (CFG)
Parsing Process
Types of Parsing
Transition Network
Types of Transition Network
Learning - Artificial Intelligence
Classification of Learning
Multi Agent Learning
Explanation based Learning
Genetic Algorithm
Applications and Advantages of Genetic Algorithm
Neural Network
Features Of Artificial Network (ANN)
Types of Neural Networks
Feed Forward neural network
Back Propagation neural network
Clustering and Types of Clustering
Pattern Recognition
Expert System
Difference Between Expert System and Conventional System
The Development Process of an Expert System
Characteristics of an Expert System
Structure of an Expert System
Rule Based Architecture of an Expert System
Applications of Expert Sytem

For Extra Reference Notes 2


Artificial Intelligence(AI) Problem Solving
Intelligent Agent
Uninformed Search Strategies
Heuristics / Informed Search Strategies
Constraint Satisfaction Problems (CSPS)
Important Questions and Answers: Algorithm of Problem Solving
Logical Agents
Important Questions and Answers: Logical Agents
Planning With State Space Search
Partial Order Planning
Important Questions and Answers: Artificial Intelligence Planning
Uncertainty - Artificial Intelligence
Important Questions and Answers: Artificial Intelligence - Uncertainty
Learning from observation
Inductive Learning
Learning Decision Trees
Explanation Based Learning
Statistical Learning Methods
Reinforcement Learning
Important Questions and Answers: Artificial Intelligence Learning

For Extra Reference Notes 3


What is Artificial Intelligence(AI)?
Importance of Artificial Intelligence(AI)
Early work in Artificial Intelligence(AI)
Artificial Intelligence(AI) and related fields
Search and Control Strategies
Examples of search problems
Uniformed or Blind search
Informed search
Constraint Satisfaction Search
Heuristic Repair
Tabu Search
Simulated Annealing
Real-Time A*
Propositional and Predicate Logic
Semantics
Predicate Calculus
First-Order Predicate Logic(FOPL)
Modal Logics and Possible Worlds
Dempster- Shafer theory
Probabilistic Reasoning
Definition and importance of knowledge
Representation of knowledge
Knowledge Organization and Manipulation
Matching techniques
Structures used in Matching
Measure for Matching
Matching like Patterns
Partial Matching
The RETE matching algorithm
Knowledge Organization and Management
Indexing and retrieval techniques
Integrating knowledge and memory
Natural Language Processing
Artificial Intelligence: Grammars and Languages
Basic parsing techniques
Augmented Transition Networks
Chart Parsing
Semantic Analysis
Expert System Architecture
Rules for Knowledge Representation
Rule-Based Systems
Rule-Based Expert Systems
Architecture of an Expert System
Knowledge Engineering
CLIPS (C Language Integrated Production System)
Backward Chaining in Rule-Based Expert Systems
CYC

For Extra Reference Notes 4


What is Artificial intelligence(AI)?
Production System
Game playing
Iterative Deepening
Knowledge Representation
Predicate Calculus
Predicate Logic
AI Resolution: Definition and Principle
Structured Represntation of Knowledge
Knowledge Representation
Framework of Knowledge Representation (Poole 1998)
Knowledge Representation Schemes
Issues in Knowledge Representation
KR Using Predicate Logic
KR Using Rules
Planning and Machine Learning
Symbolic Reasoning
Statistical Reasoning
Probability and Bayes’ Theorem
Certainty Factors in Rule-Based Systems
Bayesian Networks and Certainty Factors
Dempster - Shafer Theory (DST)
Fuzzy Logic
Expert System
Expert System Characteristics
Expert System Features
Knowledge Acquisition
Knowledge Base (Representing and Using Domain Knowledge)
Inference Engine
Expert System Shells
Explanation - Expert System
Application of Expert Systems

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